This specification relates to training machine learning models.
A machine learning model receives input and generates an output based on the received input and on values of the parameters of the model. For example, machine learning models may receive an image and generate a score for each of a set of classes, with the score for a given class representing a probability that the image contains an image of an object that belongs to the class.
The machine learning model may be composed of, e.g., a single level of linear or non-linear operations or may be a deep network, i.e., a machine learning model that is composed of multiple levels, one or more of which may be layers of non-linear operations. An example of a deep network is a neural network with one or more hidden layers.